Access historical weather data in Australia
Project description
ausweather
Very very very alpha - built for daily/monthly/annual rainfall initially.
Download weather data from BoM via SILO, for now.
E.g. for Kent Town annual rainfall. Find the station number using the BoM Weather Station Directory:
>>> import ausweather >>> data = ausweather.fetch_bom_station_from_silo(23090, 'kinverarity@hotmail.com') station #: 23090 name: ADELAIDE (KENT TOWN) title: 23090 ADELAIDE (KENT TOWN) (fetched from SILO on 2020-03-04 16:23:26.395696) >>> data.keys() dict_keys(['silo_returned', 'station_no', 'station_name', 'title', 'df', 'annual', 'srn']) >>> data['df'].info() RangeIndex: 25630 entries, 1 to 25630 Data columns (total 28 columns): Date 25630 non-null datetime64[ns] Day 25630 non-null int32 Date2 25630 non-null object T.Max 25630 non-null float64 Smx 25630 non-null int32 T.Min 25630 non-null float64 Smn 25630 non-null int32 Rain 25630 non-null float64 Srn 25630 non-null int32 Evap 25630 non-null float64 Sev 25630 non-null object Radn 25630 non-null float64 Ssl 25630 non-null int32 VP 25630 non-null float64 Svp 25630 non-null int32 RHmaxT 25630 non-null float64 RHminT 25630 non-null float64 FAO56 25630 non-null float64 Mlake 25630 non-null float64 Mpot 25630 non-null float64 Mact 25630 non-null float64 Mwet 25630 non-null float64 Span 25630 non-null float64 Ssp 25630 non-null int32 EvSp 25630 non-null float64 Ses 25630 non-null int32 MSLPres 25630 non-null float64 Sp 25630 non-null int32 dtypes: datetime64[ns](1), float64(16), int32(9), object(2) memory usage: 4.6+ MB >>> data['annual'].head() Date 1950 426.9 1951 677.9 1952 584.9 1953 601.0 1954 439.6 Name: Rain, dtype: float64 >>> ausweather.plot_silo_station(data['annual'], data['annual'].mean(), data['srn'])
List of changes
Version 0.2.1 (3 Mar 2020)
- Fix bug for whitespace in BoM station name
Version 0.2.0 (3 Mar 2020)
- Update, many changes.
Version 0.1.0 (11 Feb 2020)
- Initial release
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